Workspace Qdrant MCP
workspace-qdrant-mcp
Векторная база данных с привязкой к проекту для ИИ-ассистентов, обеспечивающая гибридный семантический и ключевой поиск с автоматическим обнаружением проектов.
Возможности
Гибридный поиск — сочетает семантическое сходство с сопоставлением по ключевым словам с использованием Reciprocal Rank Fusion (RRF).
Обнаружение проектов — автоматическое распознавание репозиториев Git и создание коллекций с привязкой к проекту.
6 инструментов MCP — search, retrieve, rules, store, grep, list.
Интеллектуальный анализ кода — семантическая нарезка Tree-sitter + интеграция с LSP для активных проектов.
Граф кода — граф связей с алгоритмами (PageRank, обнаружение сообществ, центральность по посредничеству).
Высокопроизводительный CLI — инструмент командной строки
wqmна языке Rust.Фоновый демон —
memexdдля непрерывного мониторинга и обработки файлов.
Related MCP server: Super-Memory-TS
Быстрый старт
Предварительные требования
Qdrant —
docker run -d -p 6333:6333 -v qdrant_storage:/qdrant/storage qdrant/qdrantC-компилятор — необходим для компиляции грамматик Tree-sitter при первом использовании. Грамматики Tree-sitter распространяются в виде исходного кода на C и компилируются локально.
macOS:
xcode-select --install(инструменты командной строки Xcode)Linux:
apt install build-essential(Debian/Ubuntu) илиdnf groupinstall "Development Tools"(Fedora)Windows: Установите Visual Studio Build Tools с рабочей нагрузкой C++.
Установка
Вариант 1: Homebrew (рекомендуется — macOS и Linux)
brew install ChrisGVE/tap/workspace-qdrant
brew services start workspace-qdrantВариант 2: Готовые бинарные файлы
# macOS / Linux
curl -fsSL https://raw.githubusercontent.com/ChrisGVE/workspace-qdrant-mcp/main/scripts/download-install.sh | bash
# Windows (PowerShell)
irm https://raw.githubusercontent.com/ChrisGVE/workspace-qdrant-mcp/main/scripts/download-install.ps1 | iexУстанавливает wqm и memexd в ~/.local/bin (Linux/macOS) или %LOCALAPPDATA%\wqm\bin (Windows).
Вариант 3: Сборка из исходного кода
git clone https://github.com/ChrisGVE/workspace-qdrant-mcp.git
cd workspace-qdrant-mcp
./install.shПодробные инструкции и примечания для конкретных платформ см. в справочнике по установке. Для Windows см. Руководство по установке в Windows.
Настройка MCP
Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"workspace-qdrant-mcp": {
"command": "node",
"args": ["/path/to/workspace-qdrant-mcp/src/typescript/mcp-server/dist/index.js"],
"env": {
"QDRANT_URL": "http://localhost:6333"
}
}
}
}Claude Code:
claude mcp add workspace-qdrant-mcp -- node /path/to/workspace-qdrant-mcp/src/typescript/mcp-server/dist/index.jsПроверка
wqm --version
wqm status healthИнтеграция с CLAUDE.md
Добавьте следующее в файл CLAUDE.md вашего проекта (или в глобальный ~/.claude/CLAUDE.md), чтобы Claude Code активно использовал workspace-qdrant:
## workspace-qdrant
The `workspace-qdrant` MCP server provides codebase-aware search, a library knowledge base, a scratchpad for accumulated insights, and persistent behavioral rules. The tool schemas are self-describing; these instructions cover *when* and *how* to use them.
### Primary Search and Knowledge Base
**Use `workspace-qdrant` first whenever context is uncertain** — first session on a project, returning after a significant gap, or exploring an unfamiliar subsystem. It is faster and more accurate than walking files manually, and it retrieves findings from prior sessions that would otherwise be lost.
**Three-step protocol:**
1. **Search** with `workspace-qdrant` (`search`, `grep`, `list`, or `retrieve`)
2. **Fall back** to `Grep`, `Glob`, `WebSearch` only when workspace-qdrant is insufficient or unavailable
3. **Store** any new findings, analysis, or design rationale via `store` so they are retrievable in future sessions
When a fresh handover or strong prior context already covers what you need, skip the exploratory search — but always store new findings at the end.
**Collections and their purpose:**
- `projects` — indexed codebase; use `scope="project"` (current project) or `scope="all"` (across all projects)
- `libraries` — external reference docs, API specs, third-party documentation; add via `store` with `collection="libraries"` and search with `includeLibraries=true`
- `scratchpad` — analysis, design rationale, research transcripts, architectural insights; complements session handovers by building a growing, semantically searchable knowledge layer across sessions
- `rules` — persistent behavioral rules; load at session start via `rules` → `action="list"`
**Practical notes:**
- Use `grep` for exact strings or regex; `list` with `format="summary"` to explore project structure
- Store external docs or specs into `libraries` so they are searchable alongside code
- Use the scratchpad to record *why* decisions were made, not just *what* was done — future sessions can retrieve the reasoning
### Sub-Agents
Sub-agents start with only the prompt you give them — they have no session history or handover context. They must always use `workspace-qdrant` first for any code exploration, without exception. Include this verbatim in every agent prompt:
> "You have no prior context about this codebase. Use `workspace-qdrant` as your mandatory first tool for ALL code searches — symbols, functions, architecture, patterns, prior findings. Use `search`, `grep`, `list`, or `retrieve` before touching any file with Read/Grep/Glob. Store any new findings, analysis, or design rationale via `store` (scratchpad for insights, libraries for reference docs) so they persist for future sessions."
### Project Registration
At session start, check whether the current project is registered with workspace-qdrant. If it is not, ask the user whether they want to register it (do not register silently). Once registered, the daemon handles file watching and ingestion automatically — no further action is needed.
### Behavioral Rules
The `rules` tool manages persistent rules that are injected into context across sessions. Rules are **user-initiated only** — add rules when the user explicitly instructs you to, never autonomously. Use `action="list"` at session start to load active rules.
### Issue Reporting
workspace-qdrant is under active development. If you encounter errors, unexpected behavior, or limitations with any workspace-qdrant tool, report them as GitHub issues at https://github.com/ChrisGVE/workspace-qdrant-mcp/issues using the `gh` CLI.Инструменты MCP
Инструмент | Назначение |
| Гибридный семантический поиск + поиск по ключевым словам по индексированному контенту |
| Прямой поиск документа по ID или фильтру метаданных |
| Управление постоянными правилами поведения |
| Хранение контента, регистрация проектов, сохранение заметок |
| Поиск точной подстроки или регулярного выражения с использованием FTS5 |
| Список файлов проекта и структура папок |
Параметры и примеры см. в справочнике по инструментам MCP.
Коллекции
Коллекция | Назначение | Изоляция |
| Код проекта и документация | Мультиарендность по |
| Справочная документация (книги, статьи, доки) | Мультиарендность по |
| Правила поведения и предпочтения | Мультиарендность по |
| Временное рабочее хранилище | Для каждой сессии |
Справочник CLI
# Service management
wqm service start # Start background daemon
wqm service status # Check daemon status
wqm status health # System health check
# Search and content
wqm search "query" # Search collections
wqm ingest file path.py # Ingest a file
wqm rules list # List behavioral rules
# Project and library
wqm project list # List registered projects
wqm project watch pause # Pause file watchers
wqm library list # List libraries
wqm tags list # List tags with counts
# Administration
wqm admin collections list # List collections
wqm admin rebuild all # Rebuild all indexes
wqm admin backup create # Backup snapshots
wqm admin stats overview # Search analytics
# Code graph
wqm graph stats --tenant <t> # Node/edge counts
wqm graph query --node-id <id> --tenant <t> --hops 2 # Related nodes
wqm graph impact --symbol <name> --tenant <t> # Impact analysis
wqm graph pagerank --tenant <t> --top-k 20 # PageRank centrality
# Setup
wqm init completions zsh # Shell completions
wqm init man install # Install man pages
wqm init hooks install # Install Claude Code hooks
# Queue and monitoring
wqm queue stats # Queue statisticsПолную документацию см. в справочнике CLI.
Конфигурация
Переменные окружения
Переменная | По умолчанию | Описание |
|
| URL сервера Qdrant |
| - | API-ключ (требуется для Qdrant Cloud) |
|
| Модель эмбеддингов |
Архитектура
+-----------------+
| Claude/Client |
+--------+--------+
|
+--------v--------+
| MCP Server | (TypeScript)
+--------+--------+
|
+--------------+--------------+
| |
+--------v--------+ +--------v--------+
| Rust Daemon | | Qdrant |
| (memexd) | | Vector Database |
+--------+--------+ +-----------------+
|
+--------v--------+
| File Watcher |
| Code Graph |
| Embeddings |
+-----------------+Демон на Rust обрабатывает отслеживание файлов, генерацию эмбеддингов, извлечение графа кода и обработку очереди. Все операции записи проходят через демон для обеспечения согласованности.
Документация
Руководства пользователя:
Быстрый старт — запуск за 5 минут
Руководство пользователя — полное руководство по использованию
Интеграция с LLM — лучшие практики для Claude
Справочные материалы:
Справочник CLI — все команды
wqmИнструменты MCP — параметры инструментов и примеры
Конфигурация — все опции и значения по умолчанию
Архитектура — обзор компонентов
См. Индекс документации для спецификаций, ADR и ресурсов для разработчиков.
Разработка
# TypeScript MCP server
cd src/typescript/mcp-server && npm install && npm run build && npm test
# Rust daemon and CLI (from src/rust/)
cargo build --release
cargo test
# Graph benchmarks
cargo bench --package workspace-qdrant-core --bench graph_bench
# Binaries output to:
# - target/release/wqm
# - target/release/memexdУчастие в разработке
См. CONTRIBUTING.md для настройки среды разработки и руководящих принципов.
Лицензия
Лицензия MIT — подробности см. в LICENSE.
Вдохновлено claude-qdrant-mcp
Available Tools
6 toolsgrepB
Search code with exact substring or regex pattern matching. Uses FTS5 trigram index for fast line-level search across indexed files.
Inputs: pattern (required), regex, caseSensitive, pathGlob, +5 more.
listA
List project files and folder structure. Shows only indexed files (excludes gitignored, node_modules, etc). Use format "summary" first to understand project layout, then drill into specific folders with the path parameter.
Inputs: path, depth, format, fileType, +7 more.
retrieveA
Retrieve documents by ID or metadata filter. Use this to access specific documents when you know the document ID. Prefer search for discovery, retrieve for known documents.
Inputs: documentId, collection, filter, limit, +3 more.
rulesA
Manage behavioral rules (add, update, remove, list). Check active rules at the start of each session to load the user's behavioral preferences. Rules persist across sessions and guide how you should work.
Inputs: action (required), content, label, scope, +5 more.
searchA
Search for documents using hybrid semantic and keyword search. Use this tool FIRST when answering questions about the user's codebase, project architecture, or stored knowledge. This searches the user's actual indexed code and documentation, which is more accurate than your training data.
Inputs: query (required), collection, mode, scope, +14 more.
storeA
Store content or register a project. Use type "library" (default) to store reference documentation, type "url" to fetch and ingest a web page, type "scratchpad" to save persistent notes/scratch space, or type "project" to register a project directory for file watching and ingestion.
Inputs: type, content, libraryName, forProject, +8 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 6 tools
Each tool targets a distinct function: grep searches code lines, list navigates files, retrieve fetches known documents, rules manages preferences, search discovers content, and store ingests content. There is no functional overlap.
All tool names are single lowercase verbs (grep, list, retrieve, rules, search, store), following a consistent and predictable pattern.
With 6 tools covering searching, navigation, retrieval, storage, and rule management, the count is well-scoped for a workspace knowledge server without being excessive or sparse.
The tool surface covers the core workflows of searching, browsing, retrieving, storing, and managing rules. One minor gap is the lack of explicit update/delete operations for stored documents, though store may allow overwriting.
Maintenance
Related MCP Connectors
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Persistent memory for AI agents. Semantic search, memory graph, W3C DID identity.
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Universal memory for AI agents and tools. Save, organize and search context anywhere.
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- AlicenseNot gradedqualityDmaintenanceLocal-first semantic memory server with project indexing for AI assistants. It enables AI assistants to store, retrieve, and search memories and project code using embeddings and vector search.68 npmMIT
- AlicenseCqualityBmaintenanceGives AI coding assistants persistent project memory and semantic code search, running fully locally with no API keys required.56MIT
- AlicenseNot gradedqualityFmaintenanceIndexes codebases into Qdrant for semantic search, enabling AI assistants to find relevant code by meaning without re-exploring the repo.MIT